Michael D. Wilson, 1994. "Measurement of Independent Variables – Hydrocarbon Emplacement, Clay Content, Textural Measurements", Reservoir Quality Assessment and Prediction in Clastic Rocks, Michael D. Wilson
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If, as suggested by numerous workers, hydrocarbon emplacement can significantly retard at least some diagenetic processes, it becomes important to quantify the influence of this variable on reservoir quality. Measurement of the effects of hydrocarbon emplacement on porosity can be accomplished using two different approaches. The simplest of these is to use present-day hydrocarbon saturations. The other approach involves reconstruction of hydrocarbon saturations from the point at which they are emplaced to the present.
Present-day saturations can be obtained in several ways. The first is by direct measurement on unextracted sidewall, conventional core, or preserved core samples. Due to the effects of drilling mud invasion and mud filtrate flushing, fluid saturations in sidewall core samples may differ significantly from in situ values. A second method involves the use of resistivity logs (for examples of this method, see Asquith, 1982). As was the case with core samples, logs may also be affected by drilling mud filtrate flushing in the near-wellbore zone. A third method is to conduct capillary pressure analyses on rotary sidewall or core samples. Knowing distance above the free-water level in the reservoir (assuming one is present), and properties of the reservoir fluids, an estimate of the hydrocarbon saturation at the depth of the sample analyzed can be obtained from a capillary pressure curve. An example of the use of the capillary pressure method of estimating saturations is given in Monicard (1980).
An understanding of saturation history is essential to an accurate assessment of the relative importance of hydrocarbon
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Reservoir Quality Assessment and Prediction in Clastic Rocks
This course is designed to emphasize the following topics: (1) Historical perspective on previous and current empirical, and geochemical methods of reservoir quality prediction; (2) Overview of diagenetic processes which significantly impact reservoir quality and those factors which act as major controls on those processes; (3) Proper design of a comprehensive or limited-focus predictive analysis of reservoir quality; (4) Methodologies for the accurate measurement of all major dependent and independent variables; (5) Data analysis techniques involved in quality control and the assessment of variability prior to performing multivariate regression; (6) Steps involved in the generation of a multivariate regression to insure that the model developed provides maximum accuracy using a minimum number of independent variables; (7) Case histories from a variety of settings illustrating application of the recommended approach to reservoir quality prediction.